main works, cli bugs

tradingagents/agents/utils/agent_utils.py

@@ -12,14 +12,22 @@ from dateutil.relativedelta import relativedelta
 from langchain_openai import ChatOpenAI
 import tradingagents.dataflows.interface as interface
 from tradingagents.default_config import DEFAULT_CONFIG
+from langchain_core.messages import HumanMessage
 
 
 def create_msg_delete():
     def delete_messages(state):
-        """To prevent message history from overflowing, regularly clear message history after a stage of the pipeline is done"""
+        """Clear messages and add placeholder for Anthropic compatibility"""
         messages = state["messages"]
-        return {"messages": [RemoveMessage(id=m.id) for m in messages]}
-
+        
+        # Remove all messages
+        removal_operations = [RemoveMessage(id=m.id) for m in messages]
+        
+        # Add a minimal placeholder message
+        placeholder = HumanMessage(content="Continue analysis")
+        
+        return {"messages": removal_operations + [placeholder]}
+    
     return delete_messages
 
 

tradingagents/agents/utils/memory.py

@@ -5,11 +5,11 @@ from openai import OpenAI
 
 class FinancialSituationMemory:
     def __init__(self, name, config):
-        if config["openai_backend"] == "http://localhost:11434/v1":
+        if config["backend_url"] == "http://localhost:11434/v1":
             self.embedding = "nomic-embed-text"
         else:
-            self.embedding = "text-embedding-ada-002"
-        self.client = OpenAI(base_url=config["openai_backend"])
+            self.embedding = "text-embedding-3-small"
+            self.client = OpenAI()
         self.chroma_client = chromadb.Client(Settings(allow_reset=True))
         self.situation_collection = self.chroma_client.create_collection(name=name)
 

tradingagents/dataflows/interface.py

@@ -704,10 +704,10 @@ def get_YFin_data(
 
 def get_stock_news_openai(ticker, curr_date):
     config = get_config()
-    client = OpenAI(base_url=config["openai_backend"])
+    client = OpenAI()
 
     response = client.responses.create(
-        model=config["quick_think_llm"],
+        model="gpt-4.1-mini",
         input=[
             {
                 "role": "system",
@@ -739,10 +739,10 @@ def get_stock_news_openai(ticker, curr_date):
 
 def get_global_news_openai(curr_date):
     config = get_config()
-    client = OpenAI(base_url=config["openai_backend"])
+    client = OpenAI()
 
     response = client.responses.create(
-        model=config["quick_think_llm"],
+        model="gpt-4.1-mini",
         input=[
             {
                 "role": "system",
@@ -774,10 +774,10 @@ def get_global_news_openai(curr_date):
 
 def get_fundamentals_openai(ticker, curr_date):
     config = get_config()
-    client = OpenAI(base_url=config["openai_backend"])
+    client = OpenAI()
 
     response = client.responses.create(
-        model=config["quick_think_llm"],
+        model="gpt-4.1-mini",
         input=[
             {
                 "role": "system",

tradingagents/default_config.py

@@ -8,9 +8,10 @@ DEFAULT_CONFIG = {
         "dataflows/data_cache",
     ),
     # LLM settings
+    "llm_provider": "openai",
     "deep_think_llm": "o4-mini",
     "quick_think_llm": "gpt-4o-mini",
-    "openai_backend": "https://api.openai.com/v1",
+    "backend_url": "https://api.openai.com/v1",
     # Debate and discussion settings
     "max_debate_rounds": 1,
     "max_risk_discuss_rounds": 1,

tradingagents/graph/trading_graph.py

@@ -7,6 +7,9 @@ from datetime import date
 from typing import Dict, Any, Tuple, List, Optional
 
 from langchain_openai import ChatOpenAI
+from langchain_anthropic import ChatAnthropic
+from langchain_google_genai import ChatGoogleGenerativeAI
+
 from langgraph.prebuilt import ToolNode
 
 from tradingagents.agents import *
@@ -55,10 +58,18 @@ class TradingAgentsGraph:
         )
 
         # Initialize LLMs
-        self.deep_thinking_llm = ChatOpenAI(model=self.config["deep_think_llm"], base_url=self.config["openai_backend"],)
-        self.quick_thinking_llm = ChatOpenAI(
-            model=self.config["quick_think_llm"], temperature=0.1, base_url=self.config["openai_backend"],
-        )
+        if self.config["llm_provider"].lower() == "openai" or self.config["llm_provider"] == "ollama" or self.config["llm_provider"] == "openrouter":
+            self.deep_thinking_llm = ChatOpenAI(model=self.config["deep_think_llm"], base_url=self.config["backend_url"])
+            self.quick_thinking_llm = ChatOpenAI(model=self.config["quick_think_llm"], base_url=self.config["backend_url"])
+        elif self.config["llm_provider"].lower() == "anthropic":
+            self.deep_thinking_llm = ChatAnthropic(model=self.config["deep_think_llm"], base_url=self.config["backend_url"])
+            self.quick_thinking_llm = ChatAnthropic(model=self.config["quick_think_llm"], base_url=self.config["backend_url"])
+        elif self.config["llm_provider"].lower() == "google":
+            self.deep_thinking_llm = ChatGoogleGenerativeAI(model=self.config["deep_think_llm"])
+            self.quick_thinking_llm = ChatGoogleGenerativeAI(model=self.config["quick_think_llm"])
+        else:
+            raise ValueError(f"Unsupported LLM provider: {self.config['llm_provider']}")
+        
         self.toolkit = Toolkit(config=self.config)
 
         # Initialize memories